Genome-Wide Association Analysis Reveals the Gene Loci of Yield Traits under Drought Stress at the Rice Reproductive Stage

Round 1

Reviewer 1 Report

The study is scientifically sound. However, it still requires thorough revision for the gene name as in L78 and throughout the manuscript especially in the discussion part should be in italics. The superscripts as in L155 should carefully be checked.

 Then minor corrections such as spelling/grammatical mistakes need to check.

Author Response

Manuscript report

 

1. The study is scientifically sound. However, it still requires thorough revision for the gene name as in L78 and throughout the manuscript especially in the discussion part should be in italics. The superscripts as in L155 should carefully be checked.

Authors Response

Point-by-point responses to the reviewers’ comments: 

 

1. The study is scientifically sound. However, it still requires thorough revision for the gene name as in L78 and throughout the manuscript especially in the discussion part should be in italics. The superscripts as in L155 should carefully be checked.

Response: Thank you for your comments. So the gene names have been revised in the text, including superscripts in L155.

Author Response File: Author Response.pdf

Reviewer 2 Report

the manuscript entitled as "Genome-wide association analysis reveals the gene loci of yield traits under drought stress at rice reproductive stage" identified several loci of drought stress in rice. however I will suggest few modifications

1. in the abstract section include the R2 values (mean value of all identified loci and range as well 

2. in the abstract section also add the phenotypical analysis results

3. from line 92 to 95 remove the name of traits

4. also remove the name of traits from the abstract section its looking very traditional

5. from line 103 to 110 i will suggest for a table. the collection and origin of rice genotypes  should be presented in a table.

6. "plants per row and 20 cm × 25 cm 115 spacing" please correct it with already literature. normally in rice it is 17 and 20 cm

7. line 116 and 117 should need to be explained in detailed. reveal the drought treatment procedure

8.  in line 155 you mention that "The R was used to draw a map of Manhattan" however Tassel can also do it. why you used R?

9. You used p = 2.55× 10-7 for identification of signficantaly associated SNPs in rice of drought stress. P-value is considered very out dated i will suggest to screen your SNPs with FDR correction or Beforoni values. both of the corrections are very precise and consider more accurate for identication of associated SNPs.

10. the haplotype analysis you mentioned in the material method section need to be explained in detailed. how did you convert your SNP Data to haplotypes?

11. remove the lies from 219 to 223. its repeated already in abstract ad methods

12. i will recommend to explain the detail biological, molecular and cellular functions of genes identifioed in your study, furthermore associate/link their functions with drought mechanism in rice.

moderate modifications are  suggested

Author Response

Manuscript report

 

the manuscript entitled as "Genome-wide association analysis reveals the gene loci of yield traits under drought stress at rice reproductive stage" identified several loci of drought stress in rice. However I will suggest few modifications

1. in the abstract section include the R2 values (mean value of all identified loci and range as well
2. in the abstract section also add the phenotypical analysis results.
3. from line 92 to 95 remove the name of traits?
4. also remove the name of traits from the abstract section its looking very traditional
5. from line 103 to 110 i will suggest for a table. the collection and origin of rice genotypes should be presented in a table.
6. "plants per row and 20 cm × 25 cm 115 spacing" please correct it with already literature. normally in rice it is 17 and 20 cm
7. line 116 and 117 should need to be explained in detailed. reveal the drought treatment procedure
8. in line 155 you mention that "The R was used to draw a map of Manhattan" however Tassel can also do it. why you used R?
9. You used p = 2.55× 10-7 for identification of signficantaly associated SNPs in rice of drought stress. P-value is considered very out dated i will suggest to screen your SNPs with FDR correction or Beforoni values. both of the corrections are very precise and consider more accurate for identication of associated SNPs.
10. the haplotype analysis you mentioned in the material method section need to be explained in detailed. how did you convert your SNP Data to haplotypes?
11. remove the lies from 219 to 223. its repeated already in abstract ad methods
12. i will recommend to explain the detail biological, molecular and cellular functions of genes identifioed in your study, furthermore associate/link their functions with drought mechanism in rice.

 

Authors Response

Point-by-point responses to the reviewers’ comments: 

 

1. in the abstract section include the R2 values (mean value of all identified loci and range as well

Response: Thank you for your comments. R2 has been added to the summary.

 

2. in the abstract section also add the phenotypical analysis results.

Response: Thank you for your comments. Phenotyping results have been added to the summary.

 

3. from line 92 to 95 remove the name of traits?

Response: Thank you for your comments. Deleted from the text.

 

4. also remove the name of traits from the abstract section its looking very traditional

Response: Thank you for your comments. Deleted from the text.

 

5. from line 103 to 110 i will suggest for a table. the collection and origin of rice genotypes should be presented in a table

Response: Thank you for your comments. It has been presented using a tabular form and is right there in Table S1.

 

6. also"plants per row and 20 cm × 25 cm 115 spacing" please correct it with already literature. normally in rice it is 17 and 20 cm

Response: Thank you for your comments. 20 cm × 25 cm is the row spacing of our initial experimental design[1,2].

 

7. line 116 and 117 should need to be explained in detailed. reveal the drought treatment procedure

Response: Thank you for your comments. Changes have been made in the text.

 

8. in line 155 you mention that "The R was used to draw a map of Manhattan" however Tassel can also do it. why you used R

Response: Thank you for your comments. Drawing in R is better, with better picture clarity. The Tassel we use is a multi-line command that can only be used with R

 

9. You used p = 2.55× 10^-7 for identification of significance associated SNPs in rice of drought stress. P-value is considered very out dated i will suggest to screen your SNPs with FDR correction or Bonferroni values. both of the corrections are very precise and consider more accurate for identication of associated SNPs

Response: Thank you for your comments. My p = 2.55× 10^-7 was obtained by applying GEC as a method, but GEC was used to get the significance threshold via Bonferroni and was modified in the text.

 

10. the haplotype analysis you mentioned in the material method section need to be explained in detailed. how did you convert your SNP Data to haplotypes

Response: Thank you for your comments. In haplotype analysis genomic blocks on each chromosome were scanned in adjacent regions using SNP data of candidate genes in our rice accession panel. significant phenotypic differences between different gene-haplotypes. Haplotypes containing at least 10 rice cultivars were used for comparative analysis. Student's t-test was performed to determine whether this locus could cause changes [3].

 

 

11. remove the lies from 219 to 223. its repeated already in abstract ad methods

Response: Thank you for your comments. Deleted from the text.

 

12. i will recommend to explain the detail biological, molecular and cellular functions of genes identifioed in your study, furthermore associate/link their functions with drought mechanism in rice.

Response: Thank you for your comments. In this paper, gene mining is carried out to lay the foundation for gene cloning. Further research on detail biological, molecular and cellular functions of genes is planned in the future, but this research needs a long time. Thank you for your understanding.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

References

1. Wang, N.; Zhang, W.; Wang, X.; Zheng, Z.; Bai, D.; Li, K.; Zhao, X.; Xiang, J.; Liang, Z.; Qian, Y.; et al. Genome-Wide Association Study of Xian Rice Grain Shape and Weight in Different Environments. Plants (Basel, Switzerland) 2023, 12, doi:10.3390/plants12132549.
2. Yanru, C.; Wenying, Z.; Xiuyun, L.; Shizhong, X.; Jianlong, X.; Zhikang, L. Simultaneous Improvement and Genetic Dissection of Drought Tolerance Using Selected Breeding Populations of Rice. Frontiers in Plant ence 2018, 9, 320-.
3. Zhang, F.; Wang, C.C.; Li, M.; Cui, Y.R.; Shi, Y.Y.; Wu, Z.C.; Hu, Z.Q.; Wang, W.S.; Xu, J.L.; Li, Z.K. The landscape of gene-CDS-haplotype diversity in rice: Properties, population organization, footprints of domestication and breeding, and implications for genetic improvement. Mol. Plant. 2021, 14, 787-804, doi:10.1016/j.molp.2021.02.003.

 

Author Response File: Author Response.pdf

Reviewer 3 Report

The manuscript entitled ‘Genome-wide association analysis reveals the gene loci of yield traits under drought stress at rice reproductive stage’ presents a genome-wide study and SNP marker analysis of 305 rice accessions which identified a series of QTLS adjacent to drought-tolerant related loci and candidate genes that have been associated with the drought response process.

 The analysis of the data is sound and logically presented and the manuscript is well structured and written.

The outcome of the study will be valuable since it provides useful information pertaining to the associations among significant drought tolerant QTLs, SNPs and candidate genes related to drought tolerance. Thus, it may enrich the genomic tools for producing improved rice genotypes in breeding programmes. In addition, it sets a basis for further investigating and exploring the molecular mechanisms underlying the process of drought stress response and drought tolerance in rice and other cereal crops.

 Overall, the work presented provides useful information to the community and merits publication.

However, certain points described below need further clarification:

 

-Is there any previous information available regarding the rice accessions under study with respect to their relative tolerance to drought stress?

Is there any reasonable correlation of this information with phenotyping information derived from this study and SNP analysis?

 

-Was there a control (normally irrigated plants) used in the drought experiment? The drought experiment should be better explained.

 

-what was the basis for selecting the 200-kb genomic region of the selected SNPs?

 

- Figure 1 legend should be described in more detail. 

 

Where is the comparison between control and drought treatments? Should not this be included in table 1?

 

-Would the data obtained so far provide any clues as to the distribution of SNPs between genic and intergenic regions?

 

-Within the candidate genes would SNPs in the coding regions affect protein structure/function?

 

-In Fig 4a, where is the promoter (white frame)?

-Please change (e,f) to (d,e) in figure legend

 

-In Figures 4, 5, 6, 7:

please change (e,f) to (d,e) in the figure legends

there are no intergenic regions shown in the diagram

please denote the white frame existing at 3’

 

- Did the four candidate genes display any differential expression between normal and drought conditions and across genotypes? Does this correlate with promoter and intron SNPs?

Will this be part of further investigations? These could be nicely speculated in the discussion.

 

 

 

 

 

 

 

 

Author Response

Manuscript report

The manuscript entitled ‘Genome-wide association analysis reveals the gene loci of yield traits under drought stress at rice reproductive stage’ presents a genome-wide study and SNP marker analysis of 305 rice accessions which identified a series of QTLs adjacent to drought-tolerant related loci and candidate genes that have been associated with the drought response process.

 The analysis of the data is sound and logically presented and the manuscript is well structured and written.

The outcome of the study will be valuable since it provides useful information pertaining to the associations among significant drought tolerant QTLs, SNPs and candidate genes related to drought tolerance. Thus, it may enrich the genomic tools for producing improved rice genotypes in breeding programmes. In addition, it sets a basis for further investigating and exploring the molecular mechanisms underlying the process of drought stress response and drought tolerance in rice and other cereal crops.

 Overall, the work presented provides useful information to the community and merits publication.

However, certain points described below need further clarification:

1. Is there any previous information available regarding the rice accessions under study with respect to their relative tolerance to drought stress?Is there any reasonable correlation of this information with phenotyping information derived from this study and SNP analysis?
2. Was there a control (normally irrigated plants) used in the drought experiment? The drought experiment should be better explained. Where is the comparison between control and drought treatments? Should not this be included in table 1?
3. what was the basis for selecting the 200-kb genomic region of the selected SNPs?
4. Figure 1 legend should be described in more detail. 
5. Would the data obtained so far provide any clues as to the distribution of SNPs between genic and intergenic regions?
6. Within the candidate genes would SNPs in the coding regions affect protein structure/function?
7. In Fig 4a, where is the promoter (white frame)?-Please change (e,f) to (d,e) in figure legend
8. In Figures 4, 5, 6, 7:please change (e,f) to (d,e) in the figure legends，there are no intergenic regions shown in the diagram，please denote the white frame existing at 3’
9. Did the four candidate genes display any differential expression between normal and drought conditions and across genotypes? Does this correlate with promoter and intron SNPs? Will this be part of further investigations? These could be nicely speculated in the discussion.

Response: Thank you for the positive comments.

Authors Response

Point-by-point responses to the reviewers’ comments: 

 

1. Is there any previous information available regarding the rice accessions under study with respect to their relative tolerance to drought stress? Is there any reasonable correlation of this information with phenotyping information derived from this study and SNP analysis?

Response: Thank you for your comments. The accessions sourced from the 3000 Rice Genome Project (3KRGP) related to drought tolerance has one study that used 226 accessions s to study root conformation and anatomical phenotypes in response to drought stress, whereas we focused on yield traits and chose different accessions s [1]. Genome-wide association studies (GWAS), based on linkage disequilibrium, statistically analyzes genotypes and observed phenotypic traits at the population level and identifies genes that may influence phenotypic traits. GWAS is an effective and commonly used method for mining genetic association studies using natural populations.

 

2. Was there a control (normally irrigated plants) used in the drought experiment? The drought experiment should be better explained？Where is the comparison between control and drought treatments? Should not this be included in table 1?

Response: Thank you for your comments. The accessions sourced from the 3000 Rice Genome Project (3KRGP) were selected for drought tolerance screening locally with the aim of screening for superior resources suitable for drought tolerance breeding utilization in the region, and combining the screening of drought tolerance resources with the work of gene mining in this study. According to the previous research [2-6], the phenotypes and SNPs of drought conditions were utilized for GWAS analysis. We have similarly analyzed relevant studies.

 

3. what was the basis for selecting the 200-kb genomic region of the selected SNPs?

Response: Thank you for your comments. Based on reported genome-wide linkage disequilibrium (LD) decay in 3KRG (Genomic variation in 3,010 diverse accessions of Asian cultivated rice.), The local LD block analysis was performed

within 200 kb upstream.

 

4. Figure 1 legend should be described in more detail.

Response: Thank you for your comments. Fig 1 has been described in detail in the text.

 

5. Would the data obtained so far provide any clues as to the distribution of SNPs between genic and intergenic regions?

Response: Thank you for your comments. Yes, it can be provided.

QTL	chr	SNP Location (bp)	location
qGYP3.1	3	27772039	intergenic regions
qGNP4.2	4	21350438	LOC_Os04g35130
qPNP11.2	11	27691415	LOC_Os11g45750
qPH6.1	6	23018981	LOC_Os06g38780

 

6. Within the candidate genes would SNPs in the coding regions affect protein structure/function?

Response: Thank you for your comments.

Trait	MSU ID	Gene ID	SNP Location (bp)	Refer ence	Altera tiive	Region	Variation type
GYP	LOC_Os11g45924	Os11g0686400	27789646	T	C	exonic	synonymous
	LOC_Os11g45924	Os11g0686450	27789790	T	C	exonic	synonymous
	LOC_Os11g45924	Os11g0686400	27790528	T	C	exonic	synonymous
	LOC_Os11g45924	Os11g0686400	27790542	G	C	exonic	nonsynonymous
	LOC_Os11g45924	Os11g0686400	27790568	G	A	exonic	nonsynonymous
	LOC_Os11g45924	Os11g0686400	27790664	A	G	exonic	nonsynonymous
	LOC_Os11g45924	Os11g0686400	27791639	T	A	exonic	nonsynonymous
	LOC_Os11g45924	Os11g0686400	27791863	C	T	exonic	synonymous
	LOC_Os11g45924	Os11g0686400	27791915	T	C	exonic	synonymous
	LOC_Os11g45924	Os11g0686400	27791929	A	G	exonic	synonymous
GNP	LOC_Os03g48890	Os03g0695300	27843772	C	T	exonic	nonsynonymous
PNP	LOC_Os04g35114	Os04g0430400	21340854	C	T	exonic	synonymous
	LOC_Os04g35114	Os04g0430400	21340929	G	A	exonic	synonymous
	LOC_Os04g35114	Os04g0430400	21343945	G	A	exonic	synonymous
	LOC_Os04g35114	Os04g0430400	21344328	G	C	exonic	nonsynonymous
PH	LOC_Os06g38950	Os06g0589300	21340854	G	A	exonic	synonymous
	LOC_Os06g38950	Os06g0589300	21340854	A	G	exonic	synonymous

 

 

7. In Fig 4a, where is the promoter (white frame)？ Please change (e,f) to (d,e) in figure legend?

Response: Thank you for your comments. Promoter has been deleted and d, e have been modified

 

8. In Figures 4, 5, 6, 7:please change (e,f) to (d,e) in the figure legends，there are no intergenic regions shown in the diagram，please denote the white frame existing at 3’

Response: Thank you for your comments. The modification has been completed in the text.

 

9. Did the four candidate genes display any differential expression between normal and drought conditions and across genotypes? Does this correlate with promoter and intron SNPs? Will this be part of further investigations? These could be nicely speculated in the discussion.

Response: Thank you for your comments. We plan to carry out some transcriptome analysis to explore the expression differences under normal and drought conditions, cloning and functional analysis of genes, which takes a long time, thank you for your understanding.

 

 

 

 

References

1. Siangliw, J.L.; Thunnom, B.; Natividad, M.A.; Quintana, M.R.; Chebotarov, D.; McNally, K.L.; Lynch, J.P.; Brown, K.M.; Henry, A. Response of Southeast Asian rice root architecture and anatomy phenotypes to drought stress. Frontiers in Plant Science 2022, 13, 18, doi:10.3389/fpls.2022.1008954.
2. Ahmad, H.; Zafar, S.A.; Naeem, M.K.; Shokat, S.; Inam, S.; Naveed, A.S.; Xu, J.; Li, Z.; Ali, G.M.; Khan, M.R. Impact of pre-anthesis drought stress on physiology, yield-related traits and drought responsive genes in green super rice. 2021.
3. Saumya; Ranjan; Barik; Elssa; Pandit; Sharat; Kumar; Pradhan; Shakti; Prakash. Genetic mapping of morpho-physiological traits involved during reproductive stage drought tolerance in rice. PLoS One 2019, 14, e0214979.
4. Qiaojun, L.; Liang, C.; Hanwei, M.; Haibin, W.; Fangjun, F.; Pei, W.; Hui, X.; Tiemei, L.; Lijun, L. Quantitative trait locus mapping of deep rooting by linkage and association analysis in rice. J. Exp. Bot. 2015, 4749.
5. Verma, H.; Sarma, R.N. Identification of Markers for Root Traits Related to Drought Tolerance Using Traditional Rice Germplasm. Molecular Biotechnology, 1-13.
6. Uttam, B.; Subudhi, P.K. Genetic analysis of yield and agronomic traits under reproductive stage drought stress in rice using a high-resolution linkage map. Gene 2018, 669, 69-76.

 

Author Response File: Author Response.pdf